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Titlebook: Genetic Programming; 24th European Confer Ting Hu,Nuno Louren?o,Eric Medvet Conference proceedings 2021 Springer Nature Switzerland AG 2021

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發(fā)表于 2025-3-23 12:47:14 | 只看該作者
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發(fā)表于 2025-3-23 17:47:56 | 只看該作者
Regenerating Soft Robots Through Neural Cellular Automatathat are damaged to partially regenerate their original morphology through local cell interactions alone and regain some of their ability to locomote. These results take a step towards equipping artificial systems with regenerative capacities and could potentially allow for more robust operations in
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發(fā)表于 2025-3-23 21:31:58 | 只看該作者
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發(fā)表于 2025-3-24 05:08:02 | 只看該作者
On the Generalizability of Programs Synthesized by Grammar-Guided Genetic Programmingheless, the generalizability can be improved when we do not stop a GP run as usual after a first program is found that solves all training cases correctly, but give GP more time to find further solution candidates (also solving correctly all training cases) and select the smallest program (measured
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發(fā)表于 2025-3-24 08:21:52 | 只看該作者
Evolution of Complex Combinational Logic Circuits Using Grammatical Evolution with SystemVerilogur use of an HDL permits us to operate at a far higher level of abstraction than most other approaches. This has the additional benefit that no further evolutionary experiments are needed to design different input bit-width sizes of the same circuit as is the case for existing EHW approaches. Thus,
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發(fā)表于 2025-3-24 14:38:05 | 只看該作者
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發(fā)表于 2025-3-24 17:04:07 | 只看該作者
Software Anti-patterns Detection Under Uncertainty Using a Possibilistic Evolutionary Approachclassifier in dealing with uncertain data, we propose a new possibilistic evolutionary detection method, named ADIPOK (Anti-patterns Detection and Identification using Possibilistic Optimized K-NNs), that is able to deal with label uncertainty using some concepts stemming from the Possibility theory
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發(fā)表于 2025-3-24 20:00:06 | 只看該作者
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